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AIMS_dataset_conversion

This is for images in the frames folder only.

NOTE: Some species are heavily biased in the original dataset. They are not normalized in this dataset.

  1. Generate dataset JSON
python convert_to_json.py --reduce 100 --eval_p 15 --test_p 5 --min_ann 4 --frame_meta_csv_path "frame_metadata.csv" --middle
Option Description Example Default
--reduce Percentage of dataset to use. Mainly to create smaller dataset for faster testing --reduce 100 100
--eval_p Percentage to use for evaluation --eval_p 15 15
--test_p Percentage to use for testing --test_p 5 5
--min_ann Minimum annotations an image must have before being added to the new dataset --min_ann 4 4
--frame_meta_csv_path Path to frame metadata csv --frame_meta_csv_path "frame_metadata.csv" "frame_metadata.csv"
--single_class Group all species as 1 class. Useful when counting only. --single_class False
--middle Convert to middle format. Setting false will leave the json in Detectron2 format --middle True
  1. Download images in JSON. tqdm is required. Run "pip install tqdm". Will skip already downloaded files.
python download_dataset_from_json.py --json_path "output/middle_1324_C127_test_set.json" --base_url "https://data.pawsey.org.au/download/FDFML/frames/" --download_path "frames"
  1. (Optional) Copy test images out of the dataset.
python copy_json_images_to_folder.py --json_path "output/middle_1324_C127_test_set.json" --dataset_root "frames" --destination_root "curated_dataset" --max_files 60
  1. (Optional) Preview the dataset and annotations.
python preview_annotations.py --json_path "output/middle_1324_C127_test_set.json" --dataset_root "curated_dataset" 

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